The exemplary embodiment relates to digital image processing. It finds particular application in connection with the automated extraction of regions of interest from images based on previously identified regions of interest of similar images.
Image summarization involves the selection of one or more regions of interest (ROI) in an image. There are many instances where it is desirable to extract a region of interest from a digital image which is representative of the image but which contains only a subset of the image data. These include magnifying or zooming in on a desired subject in the image, image asset management, and the like. For example, thumbnail images cropped from an original image are widely used as means of conveying information, such as identifying a source image, a document containing the image, a set of images comprising the image, or the like. In the context of web browsing, for example, a user may review thumbnail images as a way to identify potentially relevant documents related to the subject matter shown in the thumbnail image. Cropping of images is used to suit display formats, such as computer and TV screens, digital picture frames, and print sizes, such as 4×6 and 8×10. Mobile devices, such as cellular phones and MP3 players often have displays which are too small for an entire image to be displayed without significant loss of detail. Cropped images are also incorporated into documents in place of an original image where space constraints do not permit an entire image to be included or where only a portion of the image is of interest.
Simple approaches are commonly employed for cropping images, which may take the center of the image as the center of the region to crop. Other approaches exploit face or skin detection techniques and saliency maps. One problem with such approaches is that automated cropping techniques often fail to identify regions which are likely to be true regions of interest to an observer.